{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 680,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 681,
   "metadata": {},
   "outputs": [],
   "source": [
    "score_man = pd.read_excel('./18级高一体测成绩汇总.xls')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 682,
   "metadata": {},
   "outputs": [],
   "source": [
    "score_woman = pd.read_excel('./18级高一体测成绩汇总.xls',sheet_name=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 683,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女肺活量</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男50米跑</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女50米跑</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男体前屈</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女跳远</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男引体</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女仰卧</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男1000米跑</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女800米跑</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>...</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4540</th>\n",
       "      <td>100</td>\n",
       "      <td>3150</td>\n",
       "      <td>100</td>\n",
       "      <td>7.1</td>\n",
       "      <td>100</td>\n",
       "      <td>7.8</td>\n",
       "      <td>100</td>\n",
       "      <td>23.6</td>\n",
       "      <td>100</td>\n",
       "      <td>24.2</td>\n",
       "      <td>...</td>\n",
       "      <td>204</td>\n",
       "      <td>100</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100</td>\n",
       "      <td>53</td>\n",
       "      <td>100</td>\n",
       "      <td>3'30\"</td>\n",
       "      <td>100</td>\n",
       "      <td>3'24\"</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4420</th>\n",
       "      <td>95</td>\n",
       "      <td>3100</td>\n",
       "      <td>95</td>\n",
       "      <td>7.2</td>\n",
       "      <td>95</td>\n",
       "      <td>7.9</td>\n",
       "      <td>95</td>\n",
       "      <td>21.5</td>\n",
       "      <td>95</td>\n",
       "      <td>22.5</td>\n",
       "      <td>...</td>\n",
       "      <td>198</td>\n",
       "      <td>95</td>\n",
       "      <td>15.0</td>\n",
       "      <td>95</td>\n",
       "      <td>51</td>\n",
       "      <td>95</td>\n",
       "      <td>3'35\"</td>\n",
       "      <td>95</td>\n",
       "      <td>3'30\"</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4300</th>\n",
       "      <td>90</td>\n",
       "      <td>3050</td>\n",
       "      <td>90</td>\n",
       "      <td>7.3</td>\n",
       "      <td>90</td>\n",
       "      <td>8.0</td>\n",
       "      <td>90</td>\n",
       "      <td>19.4</td>\n",
       "      <td>90</td>\n",
       "      <td>20.8</td>\n",
       "      <td>...</td>\n",
       "      <td>192</td>\n",
       "      <td>90</td>\n",
       "      <td>14.0</td>\n",
       "      <td>90</td>\n",
       "      <td>49</td>\n",
       "      <td>90</td>\n",
       "      <td>3'40\"</td>\n",
       "      <td>90</td>\n",
       "      <td>3'36\"</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4050</th>\n",
       "      <td>85</td>\n",
       "      <td>2900</td>\n",
       "      <td>85</td>\n",
       "      <td>7.4</td>\n",
       "      <td>85</td>\n",
       "      <td>8.3</td>\n",
       "      <td>85</td>\n",
       "      <td>17.2</td>\n",
       "      <td>85</td>\n",
       "      <td>19.1</td>\n",
       "      <td>...</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>13.0</td>\n",
       "      <td>85</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3'47\"</td>\n",
       "      <td>85</td>\n",
       "      <td>3'43\"</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3800</th>\n",
       "      <td>80</td>\n",
       "      <td>2750</td>\n",
       "      <td>80</td>\n",
       "      <td>7.5</td>\n",
       "      <td>80</td>\n",
       "      <td>8.6</td>\n",
       "      <td>80</td>\n",
       "      <td>15.0</td>\n",
       "      <td>80</td>\n",
       "      <td>17.4</td>\n",
       "      <td>...</td>\n",
       "      <td>178</td>\n",
       "      <td>80</td>\n",
       "      <td>12.0</td>\n",
       "      <td>80</td>\n",
       "      <td>43</td>\n",
       "      <td>80</td>\n",
       "      <td>3'55\"</td>\n",
       "      <td>80</td>\n",
       "      <td>3'50\"</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "男肺活量 男肺活量  女肺活量      男50米跑      女50米跑       男体前屈       女体前屈 ...   女跳远       \\\n",
       "成绩     分数    成绩   分数    成绩   分数    成绩   分数    成绩   分数    成绩 ...    成绩   分数   \n",
       "4540  100  3150  100   7.1  100   7.8  100  23.6  100  24.2 ...   204  100   \n",
       "4420   95  3100   95   7.2   95   7.9   95  21.5   95  22.5 ...   198   95   \n",
       "4300   90  3050   90   7.3   90   8.0   90  19.4   90  20.8 ...   192   90   \n",
       "4050   85  2900   85   7.4   85   8.3   85  17.2   85  19.1 ...   185   85   \n",
       "3800   80  2750   80   7.5   80   8.6   80  15.0   80  17.4 ...   178   80   \n",
       "\n",
       "男肺活量   男引体      女仰卧      男1000米跑      女800米跑       \n",
       "成绩      成绩   分数  成绩   分数      成绩   分数     成绩   分数  \n",
       "4540  16.0  100  53  100   3'30\"  100  3'24\"  100  \n",
       "4420  15.0   95  51   95   3'35\"   95  3'30\"   95  \n",
       "4300  14.0   90  49   90   3'40\"   90  3'36\"   90  \n",
       "4050  13.0   85  46   85   3'47\"   85  3'43\"   85  \n",
       "3800  12.0   80  43   80   3'55\"   80  3'50\"   80  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 683,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_appraise = pd.read_excel('./体侧成绩评分表.xls',header=[0,1])\n",
    "score_appraise.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 684,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      4.22\n",
       "1      4.27\n",
       "2      4.15\n",
       "3      4.35\n",
       "4      3.73\n",
       "5      3.82\n",
       "6      3.90\n",
       "7      4.05\n",
       "8      4.02\n",
       "9      4.20\n",
       "10     4.00\n",
       "11     4.22\n",
       "12     3.75\n",
       "13     3.77\n",
       "14     0.00\n",
       "15     3.95\n",
       "16     4.30\n",
       "17     3.53\n",
       "18     3.93\n",
       "19     3.78\n",
       "20     3.88\n",
       "21     3.95\n",
       "22     3.70\n",
       "23     4.05\n",
       "24     4.23\n",
       "25     4.07\n",
       "26     4.07\n",
       "27     4.03\n",
       "28     3.95\n",
       "29     4.27\n",
       "       ... \n",
       "447    4.25\n",
       "448    4.60\n",
       "449    3.80\n",
       "450    3.97\n",
       "451    4.03\n",
       "452    4.03\n",
       "453    4.63\n",
       "454    0.00\n",
       "455    4.03\n",
       "456    4.43\n",
       "457    4.15\n",
       "458    3.82\n",
       "459    4.60\n",
       "460    4.62\n",
       "461    3.73\n",
       "462    3.92\n",
       "463    3.68\n",
       "464    5.48\n",
       "465    4.18\n",
       "466    4.93\n",
       "467    3.90\n",
       "468    0.00\n",
       "469    4.07\n",
       "470    3.90\n",
       "471    4.97\n",
       "472    4.38\n",
       "473    5.32\n",
       "474    3.42\n",
       "475    4.65\n",
       "476    0.00\n",
       "Name: 男1000米跑, Length: 477, dtype: float64"
      ]
     },
     "execution_count": 684,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def convert(x):\n",
    "    if type(x) == int:\n",
    "        return float(x)\n",
    "    else:\n",
    "        i,n = x.split('\\'')\n",
    "        i,n = int(i),int(n)\n",
    "        return i + n/60\n",
    "score_man['男1000米跑'] = round(score_man['男1000米跑'].map(convert),2)\n",
    "score_man['男1000米跑']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 685,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4540    3.50\n",
       "4420    3.58\n",
       "4300    3.67\n",
       "4050    3.78\n",
       "3800    3.92\n",
       "3680    4.00\n",
       "3560    4.08\n",
       "3440    4.17\n",
       "3320    4.25\n",
       "3200    4.33\n",
       "3080    4.42\n",
       "2960    4.50\n",
       "2840    4.58\n",
       "2720    4.67\n",
       "2600    4.75\n",
       "2470    5.08\n",
       "2340    5.42\n",
       "2210    5.75\n",
       "2080    6.08\n",
       "1950    6.42\n",
       "Name: (男1000米跑, 成绩), dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "4540    3.40\n",
       "4420    3.50\n",
       "4300    3.60\n",
       "4050    3.72\n",
       "3800    3.83\n",
       "3680    3.92\n",
       "3560    4.00\n",
       "3440    4.08\n",
       "3320    4.17\n",
       "3200    4.25\n",
       "3080    4.33\n",
       "2960    4.42\n",
       "2840    4.50\n",
       "2720    4.58\n",
       "2600    4.67\n",
       "2470    4.83\n",
       "2340    5.00\n",
       "2210    5.17\n",
       "2080    5.33\n",
       "1950    5.50\n",
       "Name: (女800米跑, 成绩), dtype: float64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def convert2(x):\n",
    "    i,n = x.split('\\'')\n",
    "    n,x = n.split('\"')\n",
    "    i,n = int(i),int(n)\n",
    "    return i + n/60\n",
    "score_appraise.iloc[:,-4] = round(score_appraise.iloc[:,-4].map(convert2),2)\n",
    "score_appraise.iloc[:,-2] = round(score_appraise.iloc[:,-2].map(convert2),2)\n",
    "display(score_appraise.iloc[:,-4],score_appraise.iloc[:,-2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 686,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert3(x):\n",
    "    if x == '0':\n",
    "        return np.nan\n",
    "    elif x == int :\n",
    "        return float(x)\n",
    "    else:\n",
    "        return float(x)\n",
    "score_man['男50米跑'] = score_man['男50米跑'].map(convert3)\n",
    "score_man['男跳远'] = score_man['男跳远'].map(convert3)\n",
    "score_man['男体前屈'] = score_man['男体前屈'].map(convert3)\n",
    "score_man['男引体'] = score_man['男引体'].map(convert3)\n",
    "score_man['男肺活量'] = score_man['男肺活量'].map(convert3)\n",
    "score_man['身高'] = score_man['身高'].map(convert3)\n",
    "score_man['体重'] = score_man['体重'].map(convert3)\n",
    "score_man['BMI'] = score_man['BMI'].map(convert3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 687,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert4(x):\n",
    "    for p in range(len(score_appraise['男1000米跑'])):\n",
    "        if x <= score_appraise['男1000米跑']['成绩'].iloc[0]:\n",
    "            return 100\n",
    "        elif x > score_appraise['男1000米跑']['成绩'].iloc[-1]:\n",
    "            return 0\n",
    "        elif (x > score_appraise['男1000米跑']['成绩'].iloc[p] and x <= score_appraise['男1000米跑']['成绩'].iloc[p + 1]):\n",
    "            return score_appraise['男1000米跑']['分数'].iloc[p + 1]\n",
    "        elif (x < score_appraise['男1000米跑']['成绩'].iloc[p]):\n",
    "            return score_appraise['男1000米跑']['分数'].iloc[p]\n",
    "score_man.insert(loc= 3,column= '男1000米跑分数',value= score_man['男1000米跑'].map(convert4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 688,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert5(x):\n",
    "    for p in range(len(score_appraise['男50米跑'])):\n",
    "        if x <= score_appraise['男50米跑']['成绩'].iloc[0]:\n",
    "            return 100\n",
    "        elif x > score_appraise['男50米跑']['成绩'].iloc[-1]:\n",
    "            return 0\n",
    "        elif (x > score_appraise['男50米跑']['成绩'].iloc[p] and x <= score_appraise['男50米跑']['成绩'].iloc[p + 1]):\n",
    "            return score_appraise['男50米跑']['分数'].iloc[p + 1]\n",
    "        elif (x < score_appraise['男50米跑']['成绩'].iloc[p]):\n",
    "            return score_appraise['男50米跑']['分数'].iloc[p]\n",
    "score_man.insert(loc= 5,column= '男50米跑分数',value= score_man['男50米跑'].map(convert5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 689,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert6(x):\n",
    "    for p in range(len(score_appraise['男跳远'])):\n",
    "        if x >= score_appraise['男跳远']['成绩'].iloc[0]:\n",
    "            return 100\n",
    "        elif x < score_appraise['男跳远']['成绩'].iloc[-1]:\n",
    "            return 0\n",
    "        elif (x < score_appraise['男跳远']['成绩'].iloc[p] and x >= score_appraise['男跳远']['成绩'].iloc[p + 1]):\n",
    "            return score_appraise['男跳远']['分数'].iloc[p + 1]\n",
    "        elif (x > score_appraise['男跳远']['成绩'].iloc[p]):\n",
    "            return score_appraise['男跳远']['分数'].iloc[p]\n",
    "score_man.insert(loc= 7,column= '男跳远分数',value= score_man['男跳远'].map(convert6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 690,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert7(x):\n",
    "    for p in range(len(score_appraise['男体前屈'])):\n",
    "        if x >= score_appraise['男体前屈']['成绩'].iloc[0]:\n",
    "            return 100\n",
    "        elif x < score_appraise['男体前屈']['成绩'].iloc[-1]:\n",
    "            return 0\n",
    "        elif (x < score_appraise['男体前屈']['成绩'].iloc[p] and x >= score_appraise['男体前屈']['成绩'].iloc[p + 1]):\n",
    "            return score_appraise['男体前屈']['分数'].iloc[p + 1]\n",
    "        elif (x > score_appraise['男体前屈']['成绩'].iloc[p]):\n",
    "            return score_appraise['男体前屈']['分数'].iloc[p]\n",
    "score_man.insert(loc= 9,column= '男体前屈分数',value= score_man['男体前屈'].map(convert7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 692,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert8(x):\n",
    "    for p in range(len(score_appraise['男引体'])):\n",
    "        if x >= score_appraise['男引体']['成绩'].iloc[0]:\n",
    "            return 100\n",
    "        elif x < score_appraise['男引体']['成绩'].iloc[-1]:\n",
    "            return 0\n",
    "        elif (x < score_appraise['男引体']['成绩'].iloc[p] and x >= score_appraise['男引体']['成绩'].iloc[p + 1]):\n",
    "            return score_appraise['男引体']['分数'].iloc[p + 1]\n",
    "        elif (x > score_appraise['男引体']['成绩'].iloc[p]):\n",
    "            return score_appraise['男引体']['分数'].iloc[p]\n",
    "score_man.insert(loc= 11,column= '男引体分数',value= score_man['男引体'].map(convert8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 695,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>男肺活量</th>\n",
       "      <th>男肺活量</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女肺活量</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男50米跑</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女50米跑</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男体前屈</th>\n",
       "      <th>女体前屈</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女跳远</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男引体</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女仰卧</th>\n",
       "      <th colspan=\"2\" halign=\"left\">男1000米跑</th>\n",
       "      <th colspan=\"2\" halign=\"left\">女800米跑</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>...</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "      <th>成绩</th>\n",
       "      <th>分数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4540</th>\n",
       "      <td>100</td>\n",
       "      <td>3150</td>\n",
       "      <td>100</td>\n",
       "      <td>7.1</td>\n",
       "      <td>100</td>\n",
       "      <td>7.8</td>\n",
       "      <td>100</td>\n",
       "      <td>23.6</td>\n",
       "      <td>100</td>\n",
       "      <td>24.2</td>\n",
       "      <td>...</td>\n",
       "      <td>204</td>\n",
       "      <td>100</td>\n",
       "      <td>16.0</td>\n",
       "      <td>100</td>\n",
       "      <td>53</td>\n",
       "      <td>100</td>\n",
       "      <td>3.50</td>\n",
       "      <td>100</td>\n",
       "      <td>3.40</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4420</th>\n",
       "      <td>95</td>\n",
       "      <td>3100</td>\n",
       "      <td>95</td>\n",
       "      <td>7.2</td>\n",
       "      <td>95</td>\n",
       "      <td>7.9</td>\n",
       "      <td>95</td>\n",
       "      <td>21.5</td>\n",
       "      <td>95</td>\n",
       "      <td>22.5</td>\n",
       "      <td>...</td>\n",
       "      <td>198</td>\n",
       "      <td>95</td>\n",
       "      <td>15.0</td>\n",
       "      <td>95</td>\n",
       "      <td>51</td>\n",
       "      <td>95</td>\n",
       "      <td>3.58</td>\n",
       "      <td>95</td>\n",
       "      <td>3.50</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4300</th>\n",
       "      <td>90</td>\n",
       "      <td>3050</td>\n",
       "      <td>90</td>\n",
       "      <td>7.3</td>\n",
       "      <td>90</td>\n",
       "      <td>8.0</td>\n",
       "      <td>90</td>\n",
       "      <td>19.4</td>\n",
       "      <td>90</td>\n",
       "      <td>20.8</td>\n",
       "      <td>...</td>\n",
       "      <td>192</td>\n",
       "      <td>90</td>\n",
       "      <td>14.0</td>\n",
       "      <td>90</td>\n",
       "      <td>49</td>\n",
       "      <td>90</td>\n",
       "      <td>3.67</td>\n",
       "      <td>90</td>\n",
       "      <td>3.60</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4050</th>\n",
       "      <td>85</td>\n",
       "      <td>2900</td>\n",
       "      <td>85</td>\n",
       "      <td>7.4</td>\n",
       "      <td>85</td>\n",
       "      <td>8.3</td>\n",
       "      <td>85</td>\n",
       "      <td>17.2</td>\n",
       "      <td>85</td>\n",
       "      <td>19.1</td>\n",
       "      <td>...</td>\n",
       "      <td>185</td>\n",
       "      <td>85</td>\n",
       "      <td>13.0</td>\n",
       "      <td>85</td>\n",
       "      <td>46</td>\n",
       "      <td>85</td>\n",
       "      <td>3.78</td>\n",
       "      <td>85</td>\n",
       "      <td>3.72</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3800</th>\n",
       "      <td>80</td>\n",
       "      <td>2750</td>\n",
       "      <td>80</td>\n",
       "      <td>7.5</td>\n",
       "      <td>80</td>\n",
       "      <td>8.6</td>\n",
       "      <td>80</td>\n",
       "      <td>15.0</td>\n",
       "      <td>80</td>\n",
       "      <td>17.4</td>\n",
       "      <td>...</td>\n",
       "      <td>178</td>\n",
       "      <td>80</td>\n",
       "      <td>12.0</td>\n",
       "      <td>80</td>\n",
       "      <td>43</td>\n",
       "      <td>80</td>\n",
       "      <td>3.92</td>\n",
       "      <td>80</td>\n",
       "      <td>3.83</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "男肺活量 男肺活量  女肺活量      男50米跑      女50米跑       男体前屈       女体前屈 ...   女跳远       \\\n",
       "成绩     分数    成绩   分数    成绩   分数    成绩   分数    成绩   分数    成绩 ...    成绩   分数   \n",
       "4540  100  3150  100   7.1  100   7.8  100  23.6  100  24.2 ...   204  100   \n",
       "4420   95  3100   95   7.2   95   7.9   95  21.5   95  22.5 ...   198   95   \n",
       "4300   90  3050   90   7.3   90   8.0   90  19.4   90  20.8 ...   192   90   \n",
       "4050   85  2900   85   7.4   85   8.3   85  17.2   85  19.1 ...   185   85   \n",
       "3800   80  2750   80   7.5   80   8.6   80  15.0   80  17.4 ...   178   80   \n",
       "\n",
       "男肺活量   男引体      女仰卧      男1000米跑      女800米跑       \n",
       "成绩      成绩   分数  成绩   分数      成绩   分数     成绩   分数  \n",
       "4540  16.0  100  53  100    3.50  100   3.40  100  \n",
       "4420  15.0   95  51   95    3.58   95   3.50   95  \n",
       "4300  14.0   90  49   90    3.67   90   3.60   90  \n",
       "4050  13.0   85  46   85    3.78   85   3.72   85  \n",
       "3800  12.0   80  43   80    3.92   80   3.83   80  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 695,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "score_appraise.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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